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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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<div class="textblock">Here is a list of all class members with links to the classes they belong to:</div>

<h3><a id="index_s" name="index_s"></a>- s -</h3><ul>
<li>s2do()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#a5a4d6d3ff5c8acbd809108786e973f7a">shark::QpConfig</a></li>
<li>sample()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#a33b62103b6bbf8be68d767fe87b8d6e8">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a4fb877667051839acace46a03ca16e41">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#ae2228ae158c0d70b468830469bfe90e6">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#a11e7d48c8d1b8faf811d3870d9ce818a">shark::GaussianLayer</a>, <a class="el" href="structshark_1_1_hypervolume_contribution_approximator_1_1_point.html#ae981a10ff5d4c192da3a158757f18f4a">shark::HypervolumeContributionApproximator::Point&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_markov_chain.html#ab42a842328c4ac25b4b18725c7cc9e03">shark::MarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#ae9c9fbdf0f08ef6a805be89c0d891fbd">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>SampleBatch&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a0440df45c63b02e09d72f4cfd9781b2d">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_markov_chain.html#a2c380a5ddc78c38806410695e4034013">shark::MarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#af3c35158845cdeba9085921999345885">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>sampleHidden()&#160;:&#160;<a class="el" href="classshark_1_1_gibbs_operator.html#ab653cc8b59970aa87a87c9c633ed3c14">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>samples()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a20fc0a86084c2e52e4c6b06c223bb21f">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_markov_chain.html#a2453c2aaca5d5f70c4d22d47b24bc667">shark::MarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#a38ea16dcdd1a7f8182ff95fba7b34554">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>sampleVisible()&#160;:&#160;<a class="el" href="classshark_1_1_gibbs_operator.html#a4e93543dc92f11037c60bedb0451d9be">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>sampleZ()&#160;:&#160;<a class="el" href="classshark_1_1_variational_autoencoder_error.html#ac5d3fa3f5711e3556e83d536e2e4bcb9">shark::VariationalAutoencoderError&lt; SearchPointType &gt;</a></li>
<li>save()&#160;:&#160;<a class="el" href="classshark_1_1_i_serializable.html#a5bf66fa8db15cc529bec98976a2f5255">shark::ISerializable</a></li>
<li>scaleBoxConstraints()&#160;:&#160;<a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#abb019d7a60a63b0555442f946fc346e3">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a>, <a class="el" href="classshark_1_1_boxed_s_v_m_problem.html#ac9d26f5923f47708bdb22c58931501c8">shark::BoxedSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_c_s_v_m_problem.html#a5a44566d73a4d27244042719707a2779">shark::CSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_general_quadratic_problem.html#ab443ebce2edcc29998fdc12ad1e59ea5">shark::GeneralQuadraticProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#a0390d19fab99eb4c47afd40ce22deb81">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>ScaledKernel()&#160;:&#160;<a class="el" href="classshark_1_1_scaled_kernel.html#a8d5c8bd1b104f323b14c6f8178fe00b1">shark::ScaledKernel&lt; InputType &gt;</a></li>
<li>Schwefel()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_schwefel.html#ad9d6f14884a23d51c02feea6c69af263">shark::benchmarks::Schwefel</a></li>
<li>searchPoint()&#160;:&#160;<a class="el" href="classshark_1_1_individual.html#a8d6ed0dfa38f5b0e9debdeb5529e6689">shark::Individual&lt; PointType, FitnessTypeT, Chromosome &gt;</a></li>
<li>SearchPointType&#160;:&#160;<a class="el" href="classshark_1_1_abstract_multi_objective_optimizer.html#afb3194f31ebd7c2233fb4e3bc83c4777">shark::AbstractMultiObjectiveOptimizer&lt; PointTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_objective_function.html#a59bfea031628e16737c66e7117eba7b5">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a>, <a class="el" href="classshark_1_1_abstract_optimizer.html#abea8df343e5638782a9a82403adb5ae1">shark::AbstractOptimizer&lt; PointType, ResultT, SolutionTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_single_objective_optimizer.html#a85f0d04fdfb094dba4dc80b1fb5e3adb">shark::AbstractSingleObjectiveOptimizer&lt; PointType &gt;</a>, <a class="el" href="classshark_1_1_evaluation_archive.html#a3576a0054d19eaec3167458cb2f88c4a">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a>, <a class="el" href="classshark_1_1_individual.html#aa96e1866f7225504ba5a69965dd9d768">shark::Individual&lt; PointType, FitnessTypeT, Chromosome &gt;</a>, <a class="el" href="structshark_1_1_result_set.html#a98235d340d7642d8a5a3be9da541f742">shark::ResultSet&lt; SearchPointT, ResultT &gt;</a>, <a class="el" href="structshark_1_1_single_objective_result_set.html#a9f9776536d60085bea0a185d15dbdb96">shark::SingleObjectiveResultSet&lt; SearchPointTypeT &gt;</a></li>
<li>SecondOrderDerivative&#160;:&#160;<a class="el" href="classshark_1_1_evaluation_archive.html#ac343cf727f5a1f25edc6abd7c2196298">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a></li>
<li>seconds&#160;:&#160;<a class="el" href="structshark_1_1_qp_solution_properties.html#a965ff3df7a7c9ae101b0b06e82921c91">shark::QpSolutionProperties</a></li>
<li>selected()&#160;:&#160;<a class="el" href="classshark_1_1_individual.html#ae398d51a6c688bc9458694d9d47759d1">shark::Individual&lt; PointType, FitnessTypeT, Chromosome &gt;</a></li>
<li>selectionSize()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#a6644bf8a37821ba5bf71c442b99d61ab">shark::CrossEntropyMethod</a></li>
<li>selectWorkingSet()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_box_decomp.html#af243a2c18c76b3ee74d1729b3172cad8">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a8304e5a2955859682a416bc28c3d743f">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>serialize()&#160;:&#160;<a class="el" href="structshark_1_1_additive_epsilon_indicator.html#a94529f7965a68a59b3a146a2f83f4654">shark::AdditiveEpsilonIndicator</a>, <a class="el" href="structshark_1_1_bitflip_mutator.html#aba44f8e8cf6821f292275159de2f6a38">shark::BitflipMutator</a>, <a class="el" href="structshark_1_1_c_a_r_tree_1_1_node.html#a7f0359db7d16743640dbd9478f8fc5f7">shark::CARTree&lt; LabelType &gt;::Node</a>, <a class="el" href="structshark_1_1_c_m_a_chromosome.html#a02412ded01f20ad747d1eac66afb1d5a">shark::CMAChromosome</a>, <a class="el" href="structshark_1_1_crowding_distance.html#a498f97698c24ee7411df3761c0c33436">shark::CrowdingDistance</a>, <a class="el" href="structshark_1_1_hypervolume_approximator.html#a6c7042a7e0d1550769cb7d841ff35c45">shark::HypervolumeApproximator</a>, <a class="el" href="structshark_1_1_hypervolume_calculator.html#a2bc35c52be301e83b4a2de2a5d8723e2">shark::HypervolumeCalculator</a>, <a class="el" href="structshark_1_1_hypervolume_contribution.html#a9bc3edc57e78e822481b4a20a93e33f9">shark::HypervolumeContribution</a>, <a class="el" href="structshark_1_1_hypervolume_contribution_approximator.html#afd86ee5e8fa2705b792017a024295c0c">shark::HypervolumeContributionApproximator</a>, <a class="el" href="structshark_1_1_hypervolume_indicator.html#aae8e6f737532a0b949a771f9d2be4391">shark::HypervolumeIndicator</a>, <a class="el" href="structshark_1_1_indicator_based_selection.html#a6bb562cc8a260239e8c5f169920d33e4">shark::IndicatorBasedSelection&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_individual.html#a26321373a70a17256dd25214e139bfe7">shark::Individual&lt; PointType, FitnessTypeT, Chromosome &gt;</a>, <a class="el" href="structshark_1_1_key_value_pair.html#af36e24a040d7ab4927f07a66c0053a27">shark::KeyValuePair&lt; Key, Value &gt;</a>, <a class="el" href="classshark_1_1_m_o_e_a_d.html#a70d1d8439f58bdccb47cff91cc056e61">shark::MOEAD</a>, <a class="el" href="classshark_1_1_multi_nomial_distribution.html#ac13b2e76fdc95f2b115a33507b5b3b52">shark::MultiNomialDistribution</a>, <a class="el" href="classshark_1_1_multi_variate_normal_distribution.html#ac2a3b0120928a80bc26a5a7df2ac2a1b">shark::MultiVariateNormalDistribution</a>, <a class="el" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ac82104835bfa8ccecae3bfc313d5a863">shark::MultiVariateNormalDistributionCholesky</a>, <a class="el" href="structshark_1_1_n_s_g_a3_indicator.html#ab76580d0beca10b7a3df34f5895cec61">shark::NSGA3Indicator</a>, <a class="el" href="structshark_1_1_partially_mapped_crossover.html#ae1de082eed71f2d17e7467a6121ee1cd">shark::PartiallyMappedCrossover</a>, <a class="el" href="structshark_1_1_penalizing_evaluator.html#ae1ca35f5ebdc43c424826b16d52bbee7">shark::PenalizingEvaluator</a>, <a class="el" href="structshark_1_1_polynomial_mutator.html#ac2e53465e4a8a9501872b36e35bf471f">shark::PolynomialMutator</a>, <a class="el" href="structshark_1_1_reference_vector_adaptation.html#a4cf77240090562c020ad4c5093df0ccc">shark::ReferenceVectorAdaptation&lt; IndividualType &gt;</a>, <a class="el" href="structshark_1_1_reference_vector_guided_selection.html#ab8091809b0e95b77de9c89fd08ecf232">shark::ReferenceVectorGuidedSelection&lt; IndividualType &gt;</a>, <a class="el" href="structshark_1_1_result_set.html#a18325e1e0df9c5e197dafd5148a7db68">shark::ResultSet&lt; SearchPointT, ResultT &gt;</a>, <a class="el" href="classshark_1_1_r_v_e_a.html#aa2a3484f54c7c2d46331bd19c3f8c53e">shark::RVEA</a>, <a class="el" href="classshark_1_1_shape.html#a54cd223c48635388a82288a7bfb37a9c">shark::Shape</a>, <a class="el" href="structshark_1_1_simulated_binary_crossover.html#adabf150b6e3069c5bbe68c37933b110b">shark::SimulatedBinaryCrossover&lt; PointType &gt;</a>, <a class="el" href="classshark_1_1statistics_1_1_result_table.html#a23f154547b15deff3764577e3d8935da">shark::statistics::ResultTable&lt; Parameter &gt;</a>, <a class="el" href="classshark_1_1_uniform_crossover.html#aa62cdd146ab9c3258e682de1ef811fc2">shark::UniformCrossover</a>, <a class="el" href="structshark_1_1_validated_single_objective_result_set.html#a684d91ba777740a3bdb7f44aea1fbdff">shark::ValidatedSingleObjectiveResultSet&lt; SearchPointTypeT &gt;</a></li>
<li>set()&#160;:&#160;<a class="el" href="classshark_1_1_typed_flags.html#a68ce97d08af8aedd27398d8f44218e67">shark::TypedFlags&lt; Flag &gt;</a></li>
<li>setAccuracy()&#160;:&#160;<a class="el" href="classshark_1_1_lasso_regression.html#a02b6de49b279a6bb90e1fcbd213a889f">shark::LassoRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_logistic_regression.html#a5e792090a1db8d5eb4503e10bba38872">shark::LogisticRegression&lt; InputVectorType &gt;</a></li>
<li>setAdaptive()&#160;:&#160;<a class="el" href="classshark_1_1_weighted_sum_kernel.html#aa433177f587bf2a79c7ec36977f15f00">shark::WeightedSumKernel&lt; InputType &gt;</a></li>
<li>setAdaptiveAll()&#160;:&#160;<a class="el" href="classshark_1_1_weighted_sum_kernel.html#a227f996baf7f509c9cfe2e95f0ba1135">shark::WeightedSumKernel&lt; InputType &gt;</a></li>
<li>setAdaptiveWeights()&#160;:&#160;<a class="el" href="classshark_1_1_weighted_sum_kernel.html#a74cdcb5818e16690ee1088f6d5c2e77e">shark::WeightedSumKernel&lt; InputType &gt;</a></li>
<li>setAll()&#160;:&#160;<a class="el" href="classshark_1_1_typed_flags.html#a9124e60ed14841aa7e2e8c0686faa31b">shark::TypedFlags&lt; Flag &gt;</a></li>
<li>setAlpha()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_cigar.html#a5dfed844c486e7df31c9b42d3c5ab3c8">shark::benchmarks::Cigar</a>, <a class="el" href="classshark_1_1benchmarks_1_1_cigar_discus.html#a08a1f1c629187707f07dac64b3a6fca0">shark::benchmarks::CigarDiscus</a>, <a class="el" href="structshark_1_1benchmarks_1_1_discus.html#a96f408e05a44d05272d8534d43bbe6e4">shark::benchmarks::Discus</a>, <a class="el" href="classshark_1_1_gibbs_operator.html#a5b86661eecf7572addeb9c6c2ea50711">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>setAlphaStep()&#160;:&#160;<a class="el" href="classshark_1_1_two_point_step_size_adaptation.html#af20f6e58a5564dd83f8a770b99fb8124">shark::TwoPointStepSizeAdaptation</a></li>
<li>setBatchSize()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#afa0c9dd682454dfa5f3b08cf87a5ded2">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_markov_chain.html#a755918bff14a10d22afc8c78e78582d0">shark::MarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_multi_chain_approximator.html#aa08ae62e82e9db3257defdcf6bd9fb40">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#a29b2f335f3f2b0359057568556844f4a">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>setBeta()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a1d7b2d83d91b79b18274565db1f8b93b">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#af20c825470283873aa35ca48fb831069">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>setBeta1()&#160;:&#160;<a class="el" href="classshark_1_1_adam.html#ab57d8b444cd86e5fc5b67ae7c38c9ab7">shark::Adam&lt; SearchPointType &gt;</a></li>
<li>setBeta2()&#160;:&#160;<a class="el" href="classshark_1_1_adam.html#a6a33672d62b05085d9c12000c38c4ff4">shark::Adam&lt; SearchPointType &gt;</a></li>
<li>setBounds()&#160;:&#160;<a class="el" href="classshark_1_1_box_constraint_handler.html#a51bcb77430772e37ab1b464196e5e3a7">shark::BoxConstraintHandler&lt; Vector &gt;</a></li>
<li>setBudgetMaintenanceStrategy()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a4f87b77aab4f3bc93ab429994d51caf3">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setBudgetSize()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#ae45eb76dbab8216393c04a45272c078a">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setC()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html#a61480c0f4f75a280ed65c5bce0d285da">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_abstract_svm_trainer.html#a63d60b7731298e655952bbf42d1ce2d8">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a901e47531bcb1c010bbaa859a4666f11">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#a7b5805e9aedbf6a043c19aa802255837">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setCacheSize()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_svm_trainer.html#aee037566828dae85ee2e117e71121edd">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#ab17a0f3738e21dc766e74cfd6e8e05ff">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_one_class_svm_trainer.html#aee6fb33a69ff5c13c68639c7ed8d2da0">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setCentroids()&#160;:&#160;<a class="el" href="classshark_1_1_centroids.html#a45d2dd06b31f49dc53a4697e8d368693">shark::Centroids</a></li>
<li>setClassifierNorm()&#160;:&#160;<a class="el" href="classshark_1_1_missing_features_kernel_expansion.html#a71367248f174d343ec79670207d5f947">shark::MissingFeaturesKernelExpansion&lt; InputType &gt;</a></li>
<li>setComputeBinaryDerivative()&#160;:&#160;<a class="el" href="classshark_1_1_c_svm_trainer.html#a7fdb7e988fa0949ca5e96faf9c7bcf48">shark::CSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setCovarianceMatrix()&#160;:&#160;<a class="el" href="classshark_1_1_multi_variate_normal_distribution.html#a4908517c95357a454ceb2900be594a0c">shark::MultiVariateNormalDistribution</a>, <a class="el" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7eea13a233895d60e0ab27837f5f2e7c">shark::MultiVariateNormalDistributionCholesky</a></li>
<li>setData()&#160;:&#160;<a class="el" href="classshark_1_1_contrastive_divergence.html#a2471eeb8e6d309b0fa983fdbc5879d9b">shark::ContrastiveDivergence&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_exact_gradient.html#ad19d6ea347365af7fe15a38e243b1cdf">shark::ExactGradient&lt; RBMType &gt;</a>, <a class="el" href="classshark_1_1_multi_chain_approximator.html#aefcaae99947142a6dc5bc810b808ba8c">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_p_c_a.html#a52747dc693e68fe208daf290dc6b5f54">shark::PCA</a>, <a class="el" href="classshark_1_1_single_chain_approximator.html#aa73a32da08c8e47d9db9b7afbb68d7b3">shark::SingleChainApproximator&lt; MarkovChainType &gt;</a></li>
<li>setDefaultValue()&#160;:&#160;<a class="el" href="classshark_1_1_qp_sparse_array.html#acd9012fb7ee87ce9a0dfde253259e249">shark::QpSparseArray&lt; QpFloatType &gt;</a></li>
<li>setDegree()&#160;:&#160;<a class="el" href="classshark_1_1_polynomial_kernel.html#a463c3e68ff0aca75d70a3d4e6d300c1f">shark::PolynomialKernel&lt; InputType &gt;</a></li>
<li>setDimensionName()&#160;:&#160;<a class="el" href="classshark_1_1statistics_1_1_result_table.html#afe19a5e05f777ae0a4d3c1558802be60">shark::statistics::ResultTable&lt; Parameter &gt;</a></li>
<li>setDistanceWeightType()&#160;:&#160;<a class="el" href="classshark_1_1_nearest_neighbor_model.html#aad18955d8636665b356dfc82ef5013b3">shark::NearestNeighborModel&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_nearest_neighbor_model_3_01_input_type_00_01unsigned_01int_01_4.html#a740d017bb6f26e80075a345b6beef797">shark::NearestNeighborModel&lt; InputType, unsigned int &gt;</a></li>
<li>setEpochs()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#ad5bd681e0b7e4f64f8ef3f031fe15396">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#acc7519d465974fcbb2c059debcedcc8e">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#aadca064196d92cac8b8f23f210ce89c9">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a></li>
<li>setEpsilon()&#160;:&#160;<a class="el" href="classshark_1_1_adam.html#ad976d2e3215eca56dedbe305b327d405">shark::Adam&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_epsilon_svm_trainer.html#ab6bdf1036213a92736abb9930d56de5c">shark::EpsilonSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setEta()&#160;:&#160;<a class="el" href="classshark_1_1_adam.html#aa8cda0391795c0e586a5dfcef078b15e">shark::Adam&lt; SearchPointType &gt;</a></li>
<li>setEtaMinus()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#a73397b4ec932c2fff8cde203f05e75df">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>setEtaPlus()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#af14caea0cc918c17a285ab4ec1ed37df">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>setFactor()&#160;:&#160;<a class="el" href="classshark_1_1_scaled_kernel.html#ac490cef71bad929273de841755455d87">shark::ScaledKernel&lt; InputType &gt;</a></li>
<li>setGamma()&#160;:&#160;<a class="el" href="classshark_1_1_gaussian_rbf_kernel.html#a352a91e30742cfd02950472f3879eb41">shark::GaussianRbfKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_task_kernel.html#a4fa4e4f015f87d9ec01865c4f9ecbe39">shark::GaussianTaskKernel&lt; InputTypeT &gt;</a>, <a class="el" href="classshark_1_1_r_b_f_layer.html#a9cd0894ca90ba7ec7c52956c22ada23c">shark::RBFLayer</a></li>
<li>setGammaVector()&#160;:&#160;<a class="el" href="classshark_1_1_a_r_d_kernel_unconstrained.html#aa311e1b077588f823db7d0db66c815c5">shark::ARDKernelUnconstrained&lt; InputType &gt;</a></li>
<li>setHistCount()&#160;:&#160;<a class="el" href="classshark_1_1_l_b_f_g_s.html#a57f205e2184f5a1c4d57a6ac99ec94fa">shark::LBFGS&lt; SearchPointType &gt;</a></li>
<li>setInitialSigma()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a292d0d4952eb924db23f028fa2f9135d">shark::CMA</a>, <a class="el" href="classshark_1_1_c_m_s_a.html#a95a5e9de7b67cdccc30a730dda48d3a5">shark::CMSA</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#a52d9ab529c1c8dc9fd7b2b3f81e026df">shark::VDCMA</a></li>
<li>setInitialSolution()&#160;:&#160;<a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#a6e718159c7a2ae9bb6e828792da068e3">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a>, <a class="el" href="classshark_1_1_box_constrained_problem.html#a60cc7449d9f0d93d843780aa3fd36c72">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#aa19eecb264f01e1e3f8aa07640004d7b">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>setK()&#160;:&#160;<a class="el" href="classshark_1_1_contrastive_divergence.html#ad2f9ab74c8ffca4d383827161fa2df90">shark::ContrastiveDivergence&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_multi_chain_approximator.html#a0b325f5f54fb749418f5bc6d18943f4a">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_single_chain_approximator.html#a7544401c94210a0b111ce91192d62e35">shark::SingleChainApproximator&lt; MarkovChainType &gt;</a></li>
<li>setKernel()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_svm_trainer.html#a4ff39ade04048830ec052be74d185a39">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a197676a5f5247401a286c9f2c54db720">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_expansion.html#aa3050c994b3b804dc52e3cac195d927c">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#ac9b2d2d0ca5dc5bdf44194d1cbffe607">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_one_class_svm_trainer.html#a5686f3f4d8b7abee842c94ec77d66584">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setLabelOrder()&#160;:&#160;<a class="el" href="classshark_1_1_label_order.html#ac6205d51992b997a94c1eea179d6393e">shark::LabelOrder</a></li>
<li>setLambda()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a2204984f1f5de901f4c69c64a51fb765">shark::CMA</a>, <a class="el" href="classshark_1_1_c_m_s_a.html#a813505a4954cb29b98eb670d5c7ba782">shark::CMSA</a>, <a class="el" href="classshark_1_1_lasso_regression.html#ad0a5195a4cf6ad535238f9330e61abd9">shark::LassoRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#ac3f3baaf33ba5056acf4799b017ea806">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a></li>
<li>setLambda1()&#160;:&#160;<a class="el" href="classshark_1_1_logistic_regression.html#ad0cbcad123fdab3818c063388d4bd458">shark::LogisticRegression&lt; InputVectorType &gt;</a></li>
<li>setLambda2()&#160;:&#160;<a class="el" href="classshark_1_1_logistic_regression.html#a9c836fe21f4db962f7f50350ad90e4e0">shark::LogisticRegression&lt; InputVectorType &gt;</a></li>
<li>setLearningRate()&#160;:&#160;<a class="el" href="classshark_1_1_steepest_descent.html#a68b3feecb0210689c16f1b471e60a9da">shark::SteepestDescent&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_two_point_step_size_adaptation.html#a6d2d6a051012db295c5fe2ef91c6d2dc">shark::TwoPointStepSizeAdaptation</a></li>
<li>setLimits()&#160;:&#160;<a class="el" href="classshark_1_1_circle_in_square.html#abad338aadd74f9d0e7eeb6788c598c8d">shark::CircleInSquare</a></li>
<li>setLinear()&#160;:&#160;<a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#ab68691e44171a2cc4659c19c9a0125d6">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a>, <a class="el" href="classshark_1_1_box_constrained_problem.html#a93e3a2d3665ed4a8a7e51b610e41dce9">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#a9b1278df58fcf906b5395793f5bf1b33">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>setLowerBound()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a2f4512c82509097dfbb327971032c49f">shark::CMA</a></li>
<li>setMask()&#160;:&#160;<a class="el" href="classshark_1_1_one_norm_regularizer.html#aa2c69d306a8e6a541337b263c0e04df5">shark::OneNormRegularizer&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_two_norm_regularizer.html#a6db3fc2c6d5809323a4652fbe12e00cc">shark::TwoNormRegularizer&lt; SearchPointType &gt;</a></li>
<li>setMaxCachedIndex()&#160;:&#160;<a class="el" href="classshark_1_1_cached_matrix.html#af653442cee95203259116e1f4605ca35">shark::CachedMatrix&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_precomputed_matrix.html#ac06d00ae0e964df3463682ab34fcffbb">shark::PrecomputedMatrix&lt; Matrix &gt;</a></li>
<li>setMaxDelta()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#aaa0ed6fd2ea27d56ef0cb203b1ef21d2">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>setMaxDepth()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a82e8773ba20dcf97ea659ffc51713ba9">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#a8ac7b0ff4a67b29d8d098d9a737c34c1">shark::RFTrainer&lt; unsigned int &gt;</a></li>
<li>setMaxIterations()&#160;:&#160;<a class="el" href="classshark_1_1_max_iterations.html#a01a37bc2f0b76e3801fed75f699567d6">shark::MaxIterations&lt; ResultSet &gt;</a>, <a class="el" href="classshark_1_1_missing_feature_svm_trainer.html#a953a22f4fbd37a7c0ad28ec6644a0f35">shark::MissingFeatureSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_qp_config.html#aa0ebe3d3e7163bb1eb7a5f3a56b95644">shark::QpConfig</a></li>
<li>setMaxSeconds()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#a1453635db8f97cec56f4f943e31e7520">shark::QpConfig</a></li>
<li>setMcSvmType()&#160;:&#160;<a class="el" href="classshark_1_1_c_svm_trainer.html#ac9d92bc56fc0a8fa0d73631cb3cbf323">shark::CSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_linear_c_svm_trainer.html#a7de8ad805e0b63d3eca9412d8b21b578">shark::LinearCSvmTrainer&lt; InputType &gt;</a></li>
<li>setMinAccuracy()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#a435ff9b5dd3337872c2e49d46c95c417">shark::QpConfig</a></li>
<li>setMinDelta()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#aa6efebd4d0dd0203239434574e6fbd70">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>setMinMargin()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a9f083a7f478269c13cf1550e3fe0c469">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setMinSplit()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a7973029c913a68140dc5082f8c5b5678">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#a1fa08ae23d6263bc895a6a52625fe7f9">shark::RFTrainer&lt; unsigned int &gt;</a></li>
<li>setMixingRatio()&#160;:&#160;<a class="el" href="classshark_1_1_uniform_crossover.html#a40d7c3072bab9dac6f1dc0935cc4df9d">shark::UniformCrossover</a></li>
<li>setMomentum()&#160;:&#160;<a class="el" href="classshark_1_1_steepest_descent.html#aea92742aa25e250dfa2674edb522212b">shark::SteepestDescent&lt; SearchPointType &gt;</a></li>
<li>setMTry()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a26132d8880d145e1e09e0e5c5b92e53a">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#ad3c4d4e9765940e801e123de6fed5aea">shark::RFTrainer&lt; unsigned int &gt;</a></li>
<li>setMu()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#aad3d3aa0509567312d63c4a42fa90812">shark::CMA</a>, <a class="el" href="classshark_1_1_c_m_s_a.html#af843ef42c1524b922ea60a84362c937f">shark::CMSA</a></li>
<li>setNeighbors()&#160;:&#160;<a class="el" href="classshark_1_1_nearest_neighbor_model_3_01_input_type_00_01unsigned_01int_01_4.html#a5b83ba1948eb475efb39c7f29fa8be73">shark::NearestNeighborModel&lt; InputType, unsigned int &gt;</a></li>
<li>setNodeSize()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a03743949c6b502d953db82e98280de3e">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#af0462340f6a69e42aa4f790948762457">shark::RFTrainer&lt; unsigned int &gt;</a></li>
<li>setNoiseType()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#a3727ea4cd3507b6637c7dde5343fc6ef">shark::CrossEntropyMethod</a></li>
<li>setNoiseVariance()&#160;:&#160;<a class="el" href="classshark_1_1_regularization_network_trainer.html#a2577164dc6cc24401b2901ae9e3ac6e9">shark::RegularizationNetworkTrainer&lt; InputType &gt;</a></li>
<li>setNTrees()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a47b5618fe873957a5cd17ff5568361a3">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#ab5eee35787957f2a60b558ab92ed4797">shark::RFTrainer&lt; unsigned int &gt;</a></li>
<li>setNu()&#160;:&#160;<a class="el" href="classshark_1_1_one_class_svm_trainer.html#a0537206fb1c3074e39ebd0838fb5c293">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>setNumberOfObjectives()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_objective_function.html#afcb3e45b19bba4130989d7ae37200900">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z1.html#aa36f08cb83c8438b3d68c1b22c858f49">shark::benchmarks::DTLZ1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z2.html#a17742774250c5dcbd168b7238dc86cba">shark::benchmarks::DTLZ2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z3.html#ac172f9a4d5c1f23ffb35bdb2ef5c40f3">shark::benchmarks::DTLZ3</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z4.html#a3f6f58aa4c31e83754455222272036ee">shark::benchmarks::DTLZ4</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z5.html#a2f2bbf9806ae598b1f0fd98599de72c0">shark::benchmarks::DTLZ5</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z6.html#af13d3ed8ba1121f29a770ad519a397db">shark::benchmarks::DTLZ6</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z7.html#a7e6783833f09ba5d2de5472bf2fbffe6">shark::benchmarks::DTLZ7</a>, <a class="el" href="classshark_1_1_evaluation_archive.html#aaa3d16da93398793cb0b1438d1ed3725">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a></li>
<li>setNumberOfSamples()&#160;:&#160;<a class="el" href="classshark_1_1_multi_chain_approximator.html#a8647286447d32e7f2e7fc4c588b92539">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_single_chain_approximator.html#a5191876b06e803f1c6ea7accd397b6a9">shark::SingleChainApproximator&lt; MarkovChainType &gt;</a></li>
<li>setNumberOfTemperatures()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a62a2ca127f47380ec50bd859487e2e96">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#aecba5353377bf74ef5f5171c943809dc">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>setNumberOfVariables()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_objective_function.html#a4bdfc60abbe8548ba090bff096295b8f">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a>, <a class="el" href="structshark_1_1benchmarks_1_1_ackley.html#a0a14b8c5b27624c7953fa01e0e594f3d">shark::benchmarks::Ackley</a>, <a class="el" href="structshark_1_1benchmarks_1_1_cigar.html#ab50e42294ea5f1b2d6f03068d3319df0">shark::benchmarks::Cigar</a>, <a class="el" href="classshark_1_1benchmarks_1_1_cigar_discus.html#a2174c3d672907da2a808eab8cb8e5e29">shark::benchmarks::CigarDiscus</a>, <a class="el" href="structshark_1_1benchmarks_1_1_c_i_g_t_a_b1.html#abd1671bf7df0847bb3a35e41d7eb6b3f">shark::benchmarks::CIGTAB1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_c_i_g_t_a_b2.html#a945b3032f18ff14ee323af366cbe43db">shark::benchmarks::CIGTAB2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_constrained_sphere.html#a93ee871a11bc1dfb487f2f98bb0c7cfe">shark::benchmarks::ConstrainedSphere</a>, <a class="el" href="structshark_1_1benchmarks_1_1_diff_powers.html#a6ac9ff35e6859bd8691c1201dbd199bb">shark::benchmarks::DiffPowers</a>, <a class="el" href="structshark_1_1benchmarks_1_1_discus.html#a723a8b1736bc79e5f5ee3a9f6dd21efd">shark::benchmarks::Discus</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z1.html#a9b705752392171e88c5fc30d72e0fe0b">shark::benchmarks::DTLZ1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z2.html#ab3a98b7bf9aed8be1dc0e20b5d0ed9c2">shark::benchmarks::DTLZ2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z3.html#a6c5ba342ef6b84b7262ff89d02872e47">shark::benchmarks::DTLZ3</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z4.html#ad8068db643545c44e3ee8e4452f47927">shark::benchmarks::DTLZ4</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z5.html#a87a84eb1074c42742262798c3bebcdbe">shark::benchmarks::DTLZ5</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z6.html#a9c238ca026aa03406e7014c6bd3e77f7">shark::benchmarks::DTLZ6</a>, <a class="el" href="structshark_1_1benchmarks_1_1_d_t_l_z7.html#abd3c1f0abf9314cc142b463728e453fe">shark::benchmarks::DTLZ7</a>, <a class="el" href="structshark_1_1benchmarks_1_1_e_l_l_i1.html#a231e390ebdf2e75ef64cea15cbffb2ac">shark::benchmarks::ELLI1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_e_l_l_i2.html#aa2b9d8053bd55dcac7c91b47feb309fc">shark::benchmarks::ELLI2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_ellipsoid.html#a70ef10cc06e38df4e393c971d6bc80ad">shark::benchmarks::Ellipsoid</a>, <a class="el" href="structshark_1_1benchmarks_1_1_fonseca.html#a83c3656d7e090e71639fd7824b08df38">shark::benchmarks::Fonseca</a>, <a class="el" href="structshark_1_1benchmarks_1_1_g_s_p.html#a3ffa87256f022adaf2ea5550fe82bbcc">shark::benchmarks::GSP</a>, <a class="el" href="structshark_1_1benchmarks_1_1_i_h_r1.html#a7d7411aaf649d927553cb2d6156a03fa">shark::benchmarks::IHR1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_i_h_r2.html#a3a5011b68b171bdc2be98af7341268dc">shark::benchmarks::IHR2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_i_h_r3.html#a98623bb1e0c589311d7b7afa3407841d">shark::benchmarks::IHR3</a>, <a class="el" href="structshark_1_1benchmarks_1_1_i_h_r4.html#abec78a694e72d39d504a7d825924c15f">shark::benchmarks::IHR4</a>, <a class="el" href="structshark_1_1benchmarks_1_1_i_h_r6.html#ab2f79a4278218e5102d362747da8c5b6">shark::benchmarks::IHR6</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z1.html#abca225f6c07e9197a81387bd2b8a7956">shark::benchmarks::LZ1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z2.html#a0894f1c66ee4d1d5128c17c873914e48">shark::benchmarks::LZ2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z3.html#a99ba4f806ab92be2fea0bc45a94ed6bf">shark::benchmarks::LZ3</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z4.html#ac63798bae88bfb54ebc4238dc9d2a71c">shark::benchmarks::LZ4</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z5.html#a67f0adb7c9e7d5a8b28d0b480b88abd8">shark::benchmarks::LZ5</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z6.html#a51935e21dc6be70cdba62801cc18c935">shark::benchmarks::LZ6</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z7.html#a0bc46c9f0eece90a502842fb0f2b7109">shark::benchmarks::LZ7</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z8.html#a1781e54fe9d25e30cd1d48437136c1f3">shark::benchmarks::LZ8</a>, <a class="el" href="structshark_1_1benchmarks_1_1_l_z9.html#a3f7fa209d4eb376eaadf50896f926e6c">shark::benchmarks::LZ9</a>, <a class="el" href="classshark_1_1benchmarks_1_1_multi_objective_benchmark.html#a77e1305d6328c831bf14df61c37cb648">shark::benchmarks::MultiObjectiveBenchmark&lt; Objectives &gt;</a>, <a class="el" href="structshark_1_1benchmarks_1_1_rosenbrock.html#afa34ef2350b0e4499bf512c983b47207">shark::benchmarks::Rosenbrock</a>, <a class="el" href="structshark_1_1benchmarks_1_1_rotated_objective_function.html#abf5df22a0f2c0810a6a0b89d5a69cf3e">shark::benchmarks::RotatedObjectiveFunction</a>, <a class="el" href="structshark_1_1benchmarks_1_1_schwefel.html#ad37c5048dd055c79cdfae395d73d7656">shark::benchmarks::Schwefel</a>, <a class="el" href="structshark_1_1benchmarks_1_1_sphere.html#ae0769a63a040ae2a53a3c16a3e3f4027">shark::benchmarks::Sphere</a>, <a class="el" href="structshark_1_1benchmarks_1_1_z_d_t1.html#a4d209eae48ca91e0beed768aad6d4ae8">shark::benchmarks::ZDT1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_z_d_t2.html#a100b9743150d1dc27eec69c981073d45">shark::benchmarks::ZDT2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_z_d_t3.html#a29ba3e223e291dc0f8455834d313619d">shark::benchmarks::ZDT3</a>, <a class="el" href="structshark_1_1benchmarks_1_1_z_d_t4.html#ad838c97f536e2865e41c9c1e93b3d39b">shark::benchmarks::ZDT4</a>, <a class="el" href="structshark_1_1benchmarks_1_1_z_d_t6.html#a30584cda90fe58844c469b2c558af99d">shark::benchmarks::ZDT6</a>, <a class="el" href="classshark_1_1_one_norm_regularizer.html#a80a421b9bb057834c1f2d8d66e407a54">shark::OneNormRegularizer&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_two_norm_regularizer.html#a814fa121947694cf749f61960317b27a">shark::TwoNormRegularizer&lt; SearchPointType &gt;</a></li>
<li>setOffset()&#160;:&#160;<a class="el" href="classshark_1_1_qp_box_linear.html#a40ff9688a83628fbb9691f0973ea2e4b">shark::QpBoxLinear&lt; InputT &gt;</a></li>
<li>setParameterVector()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html#af04cf4a3c0d918bc9f2925d4e7839859">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_abstract_svm_trainer.html#aecde2bab6daf3fa44b94438c7ba79a24">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_a_r_d_kernel_unconstrained.html#a7e2a65001ef2e3ff14a9611ad2462dad">shark::ARDKernelUnconstrained&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_binary_layer.html#abd1f719bfde91c77f3b4580db5889427">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a18dc991922cd22819b7cb4c46f90f4f9">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_c_a_r_tree.html#a0ab54720cda5c7a9d3f571850f124725">shark::CARTree&lt; LabelType &gt;</a>, <a class="el" href="classshark_1_1_centroids.html#a130828c5db33fe9c2b8a839a972889d3">shark::Centroids</a>, <a class="el" href="classshark_1_1_classifier.html#a0a884c2aea6696bd65f9f195536c05cf">shark::Classifier&lt; 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InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_l_d_a.html#a5b65961cbc1b0a1188c74ec4fc82f60b">shark::LDA</a>, <a class="el" href="classshark_1_1_linear_kernel.html#a4c821f0c719f3033d69fd70d76546cdb">shark::LinearKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#ad7074a494d2ac2bc1bc78eb9fd2d5927">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_linear_regression.html#a0685536ee2f4abd6d739ccd86a541c41">shark::LinearRegression</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#aebbf0decaa38e3fc73a13221ec3f4a9b">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_logistic_regression.html#a99b7a94494a7544b82164c70152f7434">shark::LogisticRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_model_kernel.html#af36a8746cb716f56c3e9fedd1caedf09">shark::ModelKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_monomial_kernel.html#a7abceef7d7bc7193151948e2ca69483f">shark::MonomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_neuron_layer.html#a4d542dec8f7ec6b81f8606c7b8782267">shark::NeuronLayer&lt; NeuronType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_normalized_kernel.html#a64db356f84025fc719a02644a625c594">shark::NormalizedKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_normalizer.html#ad2beccfb155b9af3de17a2333069abd8">shark::Normalizer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_one_class_svm_trainer.html#aaba8c4daa144b68c57403b50642241c4">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_one_versus_one_classifier.html#a41b5206801f56ac6f046978b8c9f4483">shark::OneVersusOneClassifier&lt; InputType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_point_set_kernel.html#ab6f1b0f1b32868f10144497e6ff3316e">shark::PointSetKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_polynomial_kernel.html#a0a0077219b4d5eb9119151a53ff2a564">shark::PolynomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_pooling_layer.html#a11d02e430410594e67cc9f09187c172f">shark::PoolingLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_product_kernel.html#a3f63ce641b13662b6fa26d86272f80f7">shark::ProductKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_r_b_f_layer.html#a8b8883b0033bb8a18936be6ee378d866">shark::RBFLayer</a>, <a class="el" href="classshark_1_1_r_b_m.html#a4412f9b10e320b1db350284a94a4b34d">shark::RBM&lt; VisibleLayerT, HiddenLayerT, randomT &gt;</a>, <a class="el" href="classshark_1_1_resize_layer.html#a9ea41f7fa3024defb23ce0199c4a99f9">shark::ResizeLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a2172de721b6e63265d67c56076036121">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#afc8c6b93118f575b2759d72b3dd39d85">shark::RFTrainer&lt; unsigned int &gt;</a>, <a class="el" href="classshark_1_1_scaled_kernel.html#a4d0ac39729f3db9c00f87bc61ef7b3f1">shark::ScaledKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_weighted_sum_kernel.html#a3682a26ae5a4261c1be65d8d672d9252">shark::WeightedSumKernel&lt; InputType &gt;</a></li>
<li>setPrecision()&#160;:&#160;<a class="el" href="classshark_1_1_regularization_network_trainer.html#ac4eeec2481645b35732f80dc8f96f8e5">shark::RegularizationNetworkTrainer&lt; InputType &gt;</a></li>
<li>setReference()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_indicator.html#ada98460c62e1a24938ef9c7049df68ec">shark::HypervolumeIndicator</a></li>
<li>setReferencePoints()&#160;:&#160;<a class="el" href="structshark_1_1_n_s_g_a3_indicator.html#ac7b565cc0603288903fe940867016bc1">shark::NSGA3Indicator</a></li>
<li>setRegularization()&#160;:&#160;<a class="el" href="classshark_1_1_l_d_a.html#a6e5c08ed10cf6e2a95a853925a8ca41c">shark::LDA</a>, <a class="el" href="classshark_1_1_linear_regression.html#ab4781b500d756133ffc8621ee519c2ae">shark::LinearRegression</a></li>
<li>setRegularizationParameters()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_svm_trainer.html#ad3ff1a54a5eb915e631e70e26e8727ce">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a></li>
<li>setRegularizer()&#160;:&#160;<a class="el" href="classshark_1_1_contrastive_divergence.html#aee460b5ff7fc5f979bad66fd6d4c0cbc">shark::ContrastiveDivergence&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_error_function.html#af786262cd69579e9b26d28de85b8fde9">shark::ErrorFunction&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_exact_gradient.html#a3eb3523455c880a8de64e9459f29c038">shark::ExactGradient&lt; RBMType &gt;</a>, <a class="el" href="classshark_1_1_multi_chain_approximator.html#a9c9cf392354f6f6c785dc90f46d8b1b9">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_single_chain_approximator.html#a8df6ef4fa106093f126c54dc3041bd16">shark::SingleChainApproximator&lt; MarkovChainType &gt;</a></li>
<li>setRng()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_objective_function.html#a3a287178b5b0b97c71bbffc80086ff00">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a></li>
<li>setScalingCoefficients()&#160;:&#160;<a class="el" href="classshark_1_1_example_modified_kernel_matrix.html#ac1ded007da786a92cf9424048e971e9a">shark::ExampleModifiedKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_missing_features_kernel_expansion.html#aa91acaf3efe28b8895ba3bfd7af45c3a">shark::MissingFeaturesKernelExpansion&lt; InputType &gt;</a></li>
<li>setShrinking()&#160;:&#160;<a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#af9a1833825c43ee5492fde78d85cf0c5">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_box_decomp.html#a3800f70db6acd2b333addd3800c34596">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#aca9c90b5417b11327ae5447322078986">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>setSigma()&#160;:&#160;<a class="el" href="classshark_1_1_gaussian_rbf_kernel.html#a09f0c248a5fb795f26b1d3295d2d47c7">shark::GaussianRbfKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#abd76b0216a4b252eb3ef5eb40ad7ae14">shark::VDCMA</a></li>
<li>setStepSize()&#160;:&#160;<a class="el" href="classshark_1_1_two_point_step_size_adaptation.html#a65f48fafa82bd1b7a3f7e0d44137d139">shark::TwoPointStepSizeAdaptation</a></li>
<li>setStructure()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a_c_map.html#a5c3505416e7e73665b21ee7cb5a83973">shark::CMACMap</a>, <a class="el" href="classshark_1_1_conv2_d_model.html#a7e816b41a71a79b5f9da6bf304837b21">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_kernel_expansion.html#a38c97766f52bf00e5b0120c46c15f37f">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_classifier.html#abb0de810f6ea114d03217f1e9f747b41">shark::LinearClassifier&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#a901efd377ffaf2d09a50d2adcbd6f9d4">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_normalizer.html#a4ad645ce4a4509fac265a9276d9c117d">shark::Normalizer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_pooling_layer.html#ae166162c6fb2d7d079d33684ecf7e074">shark::PoolingLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_r_b_f_layer.html#a1218b1268f1cac744be2ac911fce9484">shark::RBFLayer</a>, <a class="el" href="classshark_1_1_r_b_m.html#a9ef4cbc58af54464387b84111938dd12">shark::RBM&lt; VisibleLayerT, HiddenLayerT, randomT &gt;</a>, <a class="el" href="classshark_1_1_resize_layer.html#afffd6a3b962c11a7500180f4550ae42d">shark::ResizeLayer&lt; VectorType &gt;</a></li>
<li>setSubspaceDimensions()&#160;:&#160;<a class="el" href="classshark_1_1_fisher_l_d_a.html#af8f8c3a891ece6c53cf53cf14c99bc67">shark::FisherLDA</a></li>
<li>setTargetValue()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#ac13ad894e8ac68325c6f7ebb629e644c">shark::QpConfig</a></li>
<li>setThreshold()&#160;:&#160;<a class="el" href="classshark_1_1_negative_gaussian_process_evidence.html#a73e8d2e496a680a894266fadb2c554e0">shark::NegativeGaussianProcessEvidence&lt; InputType, OutputType, LabelType &gt;</a></li>
<li>setThresholds()&#160;:&#160;<a class="el" href="classshark_1_1_negative_gaussian_process_evidence.html#aaf3ba1dfa906ef2dffe3ad08c5ae4bdb">shark::NegativeGaussianProcessEvidence&lt; InputType, OutputType, LabelType &gt;</a></li>
<li>setTrainingParameters()&#160;:&#160;<a class="el" href="classshark_1_1_r_b_f_layer.html#ab5f5fa653d9306ed7f27d415531d1b75">shark::RBFLayer</a></li>
<li>setTrainOffset()&#160;:&#160;<a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#a5cbb50a1b75f57c7dc0fe89eb28b159b">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a></li>
<li>setUniformTemperatureSpacing()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a2d6f3031dbae2513fa3bba83f261e69b">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#ad30ceacbe721d4d53e1b34a9021b602c">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>setUseBacktracking()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#a560914675f5b0cfbc089f5afb2143780">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>setUseFreezing()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#adf4586f45e4dfdab3dc01ed08e96e076">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>setUseOldValue()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#af828e4f52722599bda4f244599699d68">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>setVariance()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#a432462d9c570244fc90d6c366f495a4f">shark::CrossEntropyMethod</a></li>
<li>setWhitening()&#160;:&#160;<a class="el" href="classshark_1_1_fisher_l_d_a.html#a41aad94f4745de9e508b634d6d70a3c4">shark::FisherLDA</a>, <a class="el" href="classshark_1_1_p_c_a.html#a13027f51bff74d5b7a39d4040a9aa403">shark::PCA</a></li>
<li>setWidth()&#160;:&#160;<a class="el" href="classshark_1_1_gaussian_task_kernel.html#a0203577db9bacc51f8e9516419ae8f66">shark::GaussianTaskKernel&lt; InputTypeT &gt;</a></li>
<li>shape()&#160;:&#160;<a class="el" href="group__shark__globals.html#gabdfa24d4e424c86cf39851c143b2dd37">shark::Data&lt; Type &gt;</a></li>
<li>Shape()&#160;:&#160;<a class="el" href="classshark_1_1_shape.html#a08a3ef9a73686fab368d457696ded55e">shark::Shape</a></li>
<li>shape()&#160;:&#160;<a class="el" href="classshark_1_1_weighted_unlabeled_data.html#a928b2414d9a32987c3341743dc0716e4">shark::WeightedUnlabeledData&lt; DataT &gt;</a></li>
<li>Shark()&#160;:&#160;<a class="el" href="classshark_1_1_shark.html#a6fdaded1b30405d032656495bf28ad3d">shark::Shark</a></li>
<li>SHARK_ITERATOR_CORE_ACCESS&#160;:&#160;<a class="el" href="classshark_1_1_indexed_iterator.html#ad04e1f8c5114da431d0d97fb42329621">shark::IndexedIterator&lt; Iterator &gt;</a>, <a class="el" href="classshark_1_1_indexing_iterator.html#ad04e1f8c5114da431d0d97fb42329621">shark::IndexingIterator&lt; Container &gt;</a>, <a class="el" href="classshark_1_1_proxy_iterator.html#ad04e1f8c5114da431d0d97fb42329621">shark::ProxyIterator&lt; Sequence, ValueType, Reference &gt;</a></li>
<li>Shifter()&#160;:&#160;<a class="el" href="classshark_1_1_shifter.html#ac21cf17a7ec41054823beaac148ad979">shark::Shifter</a></li>
<li>shrink()&#160;:&#160;<a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#aaa20fc55d3f28d930e26ca577621c44d">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a>, <a class="el" href="classshark_1_1_box_constrained_problem.html#a5d8e3e168039a9f71b9b1ed0f3b9dc23">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_box_decomp.html#a9f3a0cb23c72fcc1d894cf6e052cc0a0">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#aca9f261b3af439c641c5f198ab31edc1">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#aa98f2e4bcbd2311dd36f1c28ade75bd2">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>shrinking()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#ab538a92231c05e20575f181b06c5689d">shark::QpConfig</a></li>
<li>shuffle()&#160;:&#160;<a class="el" href="group__shark__globals.html#ga96ea65352abe5e2c0787e4154a48972f">shark::LabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="group__shark__globals.html#ga67bdcaf03984f3f958b83b5a4fafe77e">shark::UnlabeledData&lt; InputT &gt;</a></li>
<li>sigma()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a65bdf7e58529550129e284b9dc4d55a3">shark::CMA</a>, <a class="el" href="classshark_1_1_c_m_s_a.html#a4c32866b77047c9599b469f610925b72">shark::CMSA</a>, <a class="el" href="classshark_1_1_elitist_c_m_a.html#a2d6e18f8d1445bcd935e98f3ff434033">shark::ElitistCMA</a>, <a class="el" href="classshark_1_1_gaussian_rbf_kernel.html#af6df6761901876c48b9318b09ceb2f49">shark::GaussianRbfKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_task_kernel.html#acddb38cbf7f7eb1ddb915020cacd9416">shark::GaussianTaskKernel&lt; InputTypeT &gt;</a>, <a class="el" href="classshark_1_1_jaakkola_heuristic.html#aa020badc9e213efd8be49004b8e8a58b">shark::JaakkolaHeuristic</a>, <a class="el" href="classshark_1_1_l_m_c_m_a.html#a226a579df53c6b4d28d854912999f667">shark::LMCMA</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#ac1319db547ccbf4d5d4fa9cd7b3487f3">shark::VDCMA</a></li>
<li>SimpleNearestNeighbors()&#160;:&#160;<a class="el" href="classshark_1_1_simple_nearest_neighbors.html#ac5425f13309ffab8422d344accddd3fa">shark::SimpleNearestNeighbors&lt; InputType, LabelType &gt;</a></li>
<li>simplex()&#160;:&#160;<a class="el" href="classshark_1_1_simplex_downhill.html#aac01e044e8c2b9c80122574751db7322">shark::SimplexDownhill</a></li>
<li>SimplexDownhill()&#160;:&#160;<a class="el" href="classshark_1_1_simplex_downhill.html#ae373497a152c2ced0c402cc6b8ddcc26">shark::SimplexDownhill</a></li>
<li>SimulatedBinaryCrossover()&#160;:&#160;<a class="el" href="structshark_1_1_simulated_binary_crossover.html#a0074ea3a7575786ae8bfdc440fe9b1c4">shark::SimulatedBinaryCrossover&lt; PointType &gt;</a></li>
<li>SingleChainApproximator()&#160;:&#160;<a class="el" href="classshark_1_1_single_chain_approximator.html#ae9205b048b7d52e6196c97e43e683ecf">shark::SingleChainApproximator&lt; MarkovChainType &gt;</a></li>
<li>SingleObjectiveResultSet()&#160;:&#160;<a class="el" href="structshark_1_1_single_objective_result_set.html#a02b2f1988c379dd17310d41a2e7f065f">shark::SingleObjectiveResultSet&lt; SearchPointTypeT &gt;</a></li>
<li>SinglePole()&#160;:&#160;<a class="el" href="classshark_1_1_single_pole.html#a7928ff59632dbc23a4b46a7d532b701e">shark::SinglePole</a></li>
<li>size()&#160;:&#160;<a class="el" href="structshark_1_1_batch_3_01shark_1_1blas_1_1compressed__vector_3_01_t_01_4_01_4.html#a5908c852091e5f4844e0ed06f359df1a">shark::Batch&lt; shark::blas::compressed_vector&lt; T &gt; &gt;</a>, <a class="el" href="classshark_1_1_binary_layer.html#ae87de45782acf5f56ed1d49c1c5f27cb">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_binary_tree.html#aa726e7311191b6617cf2079544e23662">shark::BinaryTree&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a7b10ef7574a3d07487dff51b992c3dc9">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_block_matrix2x2.html#ab4be517263cfd424033f5c999ec2c4a7">shark::BlockMatrix2x2&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_cached_matrix.html#aff0ff1f338d99ff3030a321cd292140f">shark::CachedMatrix&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_c_v_folds.html#a55e4d73aff1389cb61fc9e41fc1e92ee">shark::CVFolds&lt; DatasetTypeT &gt;</a>, <a class="el" href="classshark_1_1_data_view.html#a71ba14d4f067dc437d6683dac9982f77">shark::DataView&lt; DatasetType &gt;</a>, <a class="el" href="classshark_1_1_difference_kernel_matrix.html#a3365839ee242950f1f2e755c5634f027">shark::DifferenceKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_discrete_kernel.html#ab36fd3d4ccf16666cb6fe37f4b5e5246">shark::DiscreteKernel</a>, <a class="el" href="classshark_1_1_evaluation_archive.html#a542df27837f79d33a265a76b00c6bafd">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a>, <a class="el" href="classshark_1_1_example_modified_kernel_matrix.html#a5e0e6e172c9c67bfc192d8ed215f5ca3">shark::ExampleModifiedKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_kernel_matrix.html#ac86ec962bc2d4f3d9e8a09a18f16d06f">shark::GaussianKernelMatrix&lt; T, CacheType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#ad2a3749d604f6e425f069726cae281d1">shark::GaussianLayer</a>, <a class="el" href="classshark_1_1_kernel_matrix.html#ad2bb6df532f1e6aa39fa30f6efad5222">shark::KernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_l_r_u_cache.html#ae089a1943125f1be80d521caaefdfd0e">shark::LRUCache&lt; T &gt;</a>, <a class="el" href="classshark_1_1_modified_kernel_matrix.html#a6021c2af8651dbcd2e3a785f2b5b42f0">shark::ModifiedKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066">shark::MultiVariateNormalDistributionCholesky</a>, <a class="el" href="classshark_1_1_partly_precomputed_matrix.html#af1fe8b1e8873dfc5759d9e20ff8bd5e0">shark::PartlyPrecomputedMatrix&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_precomputed_matrix.html#a364ec759346a474311590ac8dd45093e">shark::PrecomputedMatrix&lt; Matrix &gt;</a>, <a class="el" href="structshark_1_1_qp_sparse_array_1_1_row.html#a0bb9aa2d856471d12442566d93781211">shark::QpSparseArray&lt; QpFloatType &gt;::Row</a>, <a class="el" href="classshark_1_1_regularized_kernel_matrix.html#ad45561456f338f3e1d21495030a49d5e">shark::RegularizedKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_shape.html#ac9c42cc38131c57eac4cc0a5ecf8ca4f">shark::Shape</a>, <a class="el" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">shark::WeightedDataBatch&lt; DataBatchType, WeightBatchType &gt;</a></li>
<li>SMALL_SAMPLE&#160;:&#160;<a class="el" href="classshark_1_1_p_c_a.html#ad3b450f29c9b4b265f0d16039cac8735aa87e03fd3af865af990a4fdd3f0551b3">shark::PCA</a></li>
<li>smallest()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_contribution2_d.html#a414e72cf54c537bd456e50a733ef236a">shark::HypervolumeContribution2D</a>, <a class="el" href="structshark_1_1_hypervolume_contribution3_d.html#ac4d761c1d24708031664aff96129c043">shark::HypervolumeContribution3D</a>, <a class="el" href="structshark_1_1_hypervolume_contribution.html#a46626da682183658b940865fd4589506">shark::HypervolumeContribution</a>, <a class="el" href="structshark_1_1_hypervolume_contribution_approximator.html#a5d9f9832db56f043a2f389ad5a386b55">shark::HypervolumeContributionApproximator</a>, <a class="el" href="structshark_1_1_hypervolume_contribution_m_d.html#acfeefc0f057455a384e88070a9383e5e">shark::HypervolumeContributionMD</a></li>
<li>SMALLEST&#160;:&#160;<a class="el" href="classshark_1_1_remove_budget_maintenance_strategy.html#afa4ea66adb4e0114f913bf49e9737804af408fd53121e41a537ca4280ca96e545">shark::RemoveBudgetMaintenanceStrategy&lt; InputType &gt;</a></li>
<li>SMSEMOA()&#160;:&#160;<a class="el" href="classshark_1_1_s_m_s_e_m_o_a.html#aa6096dca040f1baaba3fd313c5b3ddf6">shark::SMSEMOA</a></li>
<li>SoftClusteringModel()&#160;:&#160;<a class="el" href="classshark_1_1_soft_clustering_model.html#affdb2f86777b7ea99eab8d4b46b5bc5c">shark::SoftClusteringModel&lt; InputT &gt;</a></li>
<li>softMembership()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_clustering.html#abccfaab4d2d5c26ff5a16d7b085365d1">shark::AbstractClustering&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_centroids.html#a27c10e06b07d4e747db2cfc939020e5f">shark::Centroids</a></li>
<li>solution()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_multi_objective_optimizer.html#a88cd9d9eb6bd2edf4aa671b12024b7f2">shark::AbstractMultiObjectiveOptimizer&lt; PointTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_optimizer.html#a277acc916ab9b33a9a7fe954a7cb4b72">shark::AbstractOptimizer&lt; PointType, ResultT, SolutionTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_single_objective_optimizer.html#a0909596fcc4f80a8d108859b20b64a81">shark::AbstractSingleObjectiveOptimizer&lt; PointType &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_box_decomp.html#a6f5a77de164d1a1a378301d74cc7223c">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#aa9b4ddd02acf37a4ba2f5183e5436b79">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>solutionGradient()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_box_decomp.html#aa2b04c8858013d4258dac188781106af">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a865bba06e22ecaf94d95e3284e28c184">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>solutionProperties()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#a0ea8552b2732cbfe664b7d0706c46d80">shark::QpConfig</a></li>
<li>SolutionType&#160;:&#160;<a class="el" href="classshark_1_1_abstract_multi_objective_optimizer.html#a2b88bbfc445ce66d95cb222fdba39f07">shark::AbstractMultiObjectiveOptimizer&lt; PointTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_optimizer.html#abc94d354dbe0b99c0a69ec3e6e5e8657">shark::AbstractOptimizer&lt; PointType, ResultT, SolutionTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_single_objective_optimizer.html#a8abcd574faa4b7bd2fed03465d1eda35">shark::AbstractSingleObjectiveOptimizer&lt; PointType &gt;</a></li>
<li>solutionWeightVector()&#160;:&#160;<a class="el" href="classshark_1_1_qp_box_linear.html#a6db58d9b283d570485001ae03a9b0b87">shark::QpBoxLinear&lt; InputT &gt;</a></li>
<li>solve()&#160;:&#160;<a class="el" href="classshark_1_1_bias_solver.html#a94431a20658c032890cbb34fa0e0cba0">shark::BiasSolver&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_bias_solver_simplex.html#a60479f4edcd9038d612da5c34d4e6022">shark::BiasSolverSimplex&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_mc_pegasos.html#a559261c0f268ed08557af883e0daddfb">shark::McPegasos&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_pegasos.html#ac4d5f50755e24ff805700dd1102a3aca">shark::Pegasos&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_qp_box_linear.html#ab8274b4499b2b4c342735a3ab338e2fb">shark::QpBoxLinear&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear.html#a468f877984aab4f95122083bf4a87152">shark::QpMcLinear&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_solver.html#aef891551dc0bc92ab4571cb7d479706f">shark::QpSolver&lt; Problem, SelectionStrategy &gt;</a></li>
<li>solveSub()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_linear.html#ad1bd9cdcfb10e5aca7c77e16812bae92">shark::QpMcLinear&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_a_d_m.html#a81cde691765509bedeafe49950a4f55f">shark::QpMcLinearADM&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_a_t_m.html#a2844a08c891b42cacec77f53b4e7a1ce">shark::QpMcLinearATM&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_a_t_s.html#ab28cf05fe5056dee19e00821473f62b6">shark::QpMcLinearATS&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_c_s.html#a8de556a5e4be31c01350c6b0c125e17e">shark::QpMcLinearCS&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_l_l_w.html#a5d146ba6191a078d4d02ef0f385c1f66">shark::QpMcLinearLLW&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_m_m_r.html#a08dec16354913fbbad8e3628b608c4e1">shark::QpMcLinearMMR&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_reinforced.html#aa5609174ae0b3735e073e828f2a8839b">shark::QpMcLinearReinforced&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_w_w.html#ac24ff73630263bee2b552222196d7ca6">shark::QpMcLinearWW&lt; InputT &gt;</a></li>
<li>sparsify()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_expansion.html#a503aaebca6ce5e7d8a6f79e5e039bd9f">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_qp_config.html#a32477b55142b80bd9f82f2a2e201f5b9">shark::QpConfig</a></li>
<li>Sphere()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_sphere.html#a4ce48d4e6d13d66215c3015a06456e0e">shark::benchmarks::Sphere</a></li>
<li>splice()&#160;:&#160;<a class="el" href="group__shark__globals.html#gaabc1f57dc805faf96d59ab1ff6d4a171">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#gaf0ea94e3e28b6df4e12fcbe8040293ac">shark::LabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="group__shark__globals.html#ga26c40e65414da413dbb3ef6403b76049">shark::UnlabeledData&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_weighted_labeled_data.html#a648fe695e393366e70092d2d80cd4f62">shark::WeightedLabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="classshark_1_1_weighted_unlabeled_data.html#a71bcad4364057b3d20b6315176d6b480">shark::WeightedUnlabeledData&lt; DataT &gt;</a></li>
<li>splitBatch()&#160;:&#160;<a class="el" href="group__shark__globals.html#gaf9900fbc117dd6259136a3dd2056c11e">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#gac30b58de795e18e98901cd96b6b22d45">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>splitList()&#160;:&#160;<a class="el" href="classshark_1_1_binary_tree.html#a153a6ecae3dd8bf1407209962febca55">shark::BinaryTree&lt; InputT &gt;</a></li>
<li>squaredDistanceLowerBound()&#160;:&#160;<a class="el" href="classshark_1_1_binary_tree.html#aa78235225476effa7b22d285f3d9e197">shark::BinaryTree&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_k_d_tree.html#a68e44a697dc289c700c65658af6b3893">shark::KDTree&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_k_h_c_tree.html#a266d14a6be4ace74d919d7244a967cd8">shark::KHCTree&lt; Container, CuttingAccuracy &gt;</a>, <a class="el" href="classshark_1_1_l_c_tree.html#ada804c1f1a75c767dc6c40960172254b">shark::LCTree&lt; VectorType, CuttingAccuracy &gt;</a></li>
<li>SquaredEpsilonHingeLoss()&#160;:&#160;<a class="el" href="classshark_1_1_squared_epsilon_hinge_loss.html#a200a234a76a69808e9ed2fe42355737a">shark::SquaredEpsilonHingeLoss</a></li>
<li>SquaredHingeCSvmTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_squared_hinge_c_svm_trainer.html#a9448aa8e5bffd616d9a5ba2955b432ed">shark::SquaredHingeCSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>SquaredHingeLinearCSvmTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_squared_hinge_linear_c_svm_trainer.html#a2bfdfe17a77da644c389211a1129efff">shark::SquaredHingeLinearCSvmTrainer&lt; InputType &gt;</a></li>
<li>SquaredHingeLoss()&#160;:&#160;<a class="el" href="classshark_1_1_squared_hinge_loss.html#a9881ffee48a0cb96c693af16c21b7c92">shark::SquaredHingeLoss</a></li>
<li>SquaredLoss()&#160;:&#160;<a class="el" href="classshark_1_1_squared_loss.html#a3ff7bf885f6de94578fbc4b835a7c514">shark::SquaredLoss&lt; OutputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_squared_loss_3_01_output_type_00_01unsigned_01int_01_4.html#accc4fbbfc67fdd4cb367dab783772d2c">shark::SquaredLoss&lt; OutputType, unsigned int &gt;</a>, <a class="el" href="classshark_1_1_squared_loss_3_01_sequence_00_01_sequence_01_4.html#a8f743edb4396725b93164612b16e73ac">shark::SquaredLoss&lt; Sequence, Sequence &gt;</a></li>
<li>STANDARD&#160;:&#160;<a class="el" href="classshark_1_1_p_c_a.html#ad3b450f29c9b4b265f0d16039cac8735aa46a1b1a70f542e1569589fb42528d6d">shark::PCA</a></li>
<li>start()&#160;:&#160;<a class="el" href="classshark_1_1_timer.html#a4d88aa872b2f0eb752c01c506cc24555">shark::Timer</a></li>
<li>State&#160;:&#160;<a class="el" href="structshark_1_1_fast_sigmoid_neuron.html#a9d022ca2a90ff999ec2c8a48be81508f">shark::FastSigmoidNeuron</a>, <a class="el" href="structshark_1_1_linear_neuron.html#a25338b263dd7c7aaf03489df051c768b">shark::LinearNeuron</a>, <a class="el" href="structshark_1_1_logistic_neuron.html#acec00967da0c34f8eacb300bb25f26f6">shark::LogisticNeuron</a>, <a class="el" href="structshark_1_1_rectifier_neuron.html#aa38a1de9ef83ef387b9661ed96116299">shark::RectifierNeuron</a>, <a class="el" href="structshark_1_1_softmax_neuron.html#af038bf1643d03969d2d452a9d9b179d0">shark::SoftmaxNeuron&lt; VectorType &gt;</a>, <a class="el" href="structshark_1_1_tanh_neuron.html#acc12c52782340838b649e718de0c3507">shark::TanhNeuron</a></li>
<li>state()&#160;:&#160;<a class="el" href="structshark_1_1_two_state_space.html#a71d5152fbe88352cff723e7d5a2f9c0f">shark::TwoStateSpace&lt; State1, State2 &gt;</a></li>
<li>StateSpace&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#a0dd192fe113ecec7c0491cd7c303f1f6">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a7e97b21d8fe5817c17e2cee66c2b8760">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#a346b4d4edf91fa583578207488fc7fca">shark::GaussianLayer</a></li>
<li>statisticName()&#160;:&#160;<a class="el" href="structshark_1_1statistics_1_1_statistics.html#a2a43e43d4788db0bc6b4d294b12ed655">shark::statistics::Statistics&lt; Parameter &gt;</a></li>
<li>statistics()&#160;:&#160;<a class="el" href="classshark_1_1statistics_1_1_base_statistics_object.html#ae0b7c96f1bf4a9f7a1cb810408ac5618">shark::statistics::BaseStatisticsObject</a>, <a class="el" href="classshark_1_1statistics_1_1_fraction_missing.html#abe8988ab94d3e0f526ec44d4f9499317">shark::statistics::FractionMissing</a>, <a class="el" href="classshark_1_1statistics_1_1_mean.html#aadb8337c0352fbc315dee25517f25b3d">shark::statistics::Mean</a>, <a class="el" href="classshark_1_1statistics_1_1_quantile.html#a1f72cc7a0073f0638c8be885b0dcdacd">shark::statistics::Quantile</a></li>
<li>Statistics()&#160;:&#160;<a class="el" href="structshark_1_1statistics_1_1_statistics.html#ae35c8f063ca93f3c9d28cad6c02e7d24">shark::statistics::Statistics&lt; Parameter &gt;</a></li>
<li>statistics()&#160;:&#160;<a class="el" href="classshark_1_1statistics_1_1_variance.html#a057e285347881100d55c2b054121e13a">shark::statistics::Variance</a></li>
<li>StatisticsBatch&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#ac48b230991d6dc12efe2cd04ae7180b3">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a045a6f381a6f5d318ba718313050c19c">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#a510c15554b7b4bebec1c966e7ccaff95">shark::GaussianLayer</a></li>
<li>SteepestDescent()&#160;:&#160;<a class="el" href="classshark_1_1_steepest_descent.html#a97c32efccb3ecdb3e9b4296428d4c020">shark::SteepestDescent&lt; SearchPointType &gt;</a></li>
<li>step()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_line_search_optimizer.html#ae6689563bafd7dbbb02299e161238b26">shark::AbstractLineSearchOptimizer&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_abstract_optimizer.html#abfc507951eb09c50d62c474c79d773ea">shark::AbstractOptimizer&lt; PointType, ResultT, SolutionTypeT &gt;</a>, <a class="el" href="classshark_1_1_adam.html#aad42982976c3e91534ac33999d7c6fc3">shark::Adam&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_c_m_a.html#a4aa0ce8e2e580d20c5a99e5723e974b1">shark::CMA</a>, <a class="el" href="classshark_1_1_c_m_s_a.html#ac89303e1940fd4744a1c542bc0eeb522">shark::CMSA</a>, <a class="el" href="classshark_1_1_cross_entropy_method.html#a69f0ff106139edf53b967e7c8634471b">shark::CrossEntropyMethod</a>, <a class="el" href="classshark_1_1_elitist_c_m_a.html#afd2e76bdf537a5cdf3287c4c197e1138">shark::ElitistCMA</a>, <a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a390d4deeed260f32028b2935dd5b7ddb">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_grid_search.html#afb6458a381e6b45cb8290289a573d642">shark::GridSearch</a>, <a class="el" href="classshark_1_1_indicator_based_m_o_c_m_a.html#a5088cd38153a92dcaf45361aae621c2b">shark::IndicatorBasedMOCMA&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_indicator_based_real_coded_n_s_g_a_i_i.html#abfe4b45656f1ae018f9b6f8497117d2f">shark::IndicatorBasedRealCodedNSGAII&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_indicator_based_steady_state_m_o_c_m_a.html#a2dd77d4f60a4880e27a58e9e7101f7de">shark::IndicatorBasedSteadyStateMOCMA&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_l_m_c_m_a.html#a9e0f9265cf2592e3c88f85418457d190">shark::LMCMA</a>, <a class="el" href="classshark_1_1_markov_chain.html#af76c0b5c4c033eca275c503fa6ff8233">shark::MarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_m_o_e_a_d.html#a8742c5129a512cc1840c738457cac095">shark::MOEAD</a>, <a class="el" href="classshark_1_1_nested_grid_search.html#a6fdb96838b95142124d531921637f983">shark::NestedGridSearch</a>, <a class="el" href="classshark_1_1_point_search.html#aff93d5e557f30ffe2dd29556c84881c5">shark::PointSearch</a>, <a class="el" href="classshark_1_1_rprop.html#a9173edb5b7a84bcd46b62a46445754a6">shark::Rprop&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_r_v_e_a.html#ad62e938861ebc6b6e0749775e67c8b54">shark::RVEA</a>, <a class="el" href="classshark_1_1_simplex_downhill.html#ab1218ff639987ce11281cf4565aaa051">shark::SimplexDownhill</a>, <a class="el" href="classshark_1_1_s_m_s_e_m_o_a.html#abb385622c65f299e476a8cb5207a0ae5">shark::SMSEMOA</a>, <a class="el" href="classshark_1_1_steepest_descent.html#a481c680541979d1827c1b386203ee4e2">shark::SteepestDescent&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#af553df4a635f56eac428e064df65ccea">shark::TemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_trust_region_newton.html#aad95e74aa24a400a20829645a65615f3">shark::TrustRegionNewton</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#a9df8d807bdf57909ac6b5b5a984faf03">shark::VDCMA</a></li>
<li>stepSize()&#160;:&#160;<a class="el" href="classshark_1_1_population_based_step_size_adaptation.html#a7b9e246e1aea24500b766d2deecab993">shark::PopulationBasedStepSizeAdaptation</a>, <a class="el" href="classshark_1_1_two_point_step_size_adaptation.html#a2af42fba89576310fd19e7fc45ca4080">shark::TwoPointStepSizeAdaptation</a></li>
<li>stepVH()&#160;:&#160;<a class="el" href="classshark_1_1_gibbs_operator.html#a25136037254735170f4abf1659a0c56f">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>stop()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_stopping_criterion.html#a74a1d1aea141cf2ad5d69e29cb90f25c">shark::AbstractStoppingCriterion&lt; ResultSetT &gt;</a>, <a class="el" href="classshark_1_1_generalization_loss.html#aad6c1748d44692f8163321bb12b4e80e">shark::GeneralizationLoss&lt; PointType &gt;</a>, <a class="el" href="classshark_1_1_generalization_quotient.html#a33ce099f70c725a260a7bf19748fb15a">shark::GeneralizationQuotient&lt; PointType &gt;</a>, <a class="el" href="classshark_1_1_max_iterations.html#a3959876968fade6394247850475ad7c2">shark::MaxIterations&lt; ResultSet &gt;</a>, <a class="el" href="classshark_1_1_timer.html#ad3ccd47c0429d28d9600117b5ed57362">shark::Timer</a>, <a class="el" href="classshark_1_1_training_error.html#a37b74d5cff8620d934e90623766f7a7a">shark::TrainingError&lt; PointType &gt;</a>, <a class="el" href="classshark_1_1_training_progress.html#af320c01d4e54853e8fd3e891488bfba4">shark::TrainingProgress&lt; PointType &gt;</a>, <a class="el" href="classshark_1_1_validated_stopping_criterion.html#af9d9d15bbdebb8dbccc1f17a0eff4ccf">shark::ValidatedStoppingCriterion</a></li>
<li>stoppingCondition()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#a66fa342063f4fb0c8686a821dd14370e">shark::QpConfig</a></li>
<li>StoppingCriterionType&#160;:&#160;<a class="el" href="classshark_1_1_optimization_trainer.html#a8a059e6205b464fdfc50cf18f2799163">shark::OptimizationTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_validated_stopping_criterion.html#a705f981436596372006b07ff5b92fc87">shark::ValidatedStoppingCriterion</a></li>
<li>storeEnergyDifferences()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a5d6031a54692fdd85387eb9a2f410b22">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a></li>
<li>stream()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator_m_d_h_o_y.html#afb2637455cffec61db36d6b6dd8f6096">shark::HypervolumeCalculatorMDHOY</a></li>
<li>stride()&#160;:&#160;<a class="el" href="classshark_1_1_shape.html#af22f21df156b245f02d5729701282b75">shark::Shape</a></li>
<li>StrongNoisePtr&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#a5cd00f92f182f8045837763e93fc04c6">shark::CrossEntropyMethod</a></li>
<li>SubKernel&#160;:&#160;<a class="el" href="classshark_1_1_product_kernel.html#aa7fa5438e462e1593d8355a5ef2a6429">shark::ProductKernel&lt; InputType &gt;</a></li>
<li>SubrangeKernel()&#160;:&#160;<a class="el" href="classshark_1_1_subrange_kernel.html#af74f43289f60c804b43e0c87305b8991">shark::SubrangeKernel&lt; InputType, InnerKernel &gt;</a></li>
<li>subspaceDimensions()&#160;:&#160;<a class="el" href="classshark_1_1_fisher_l_d_a.html#a1813d2f5726649dc33a4e212ded2072e">shark::FisherLDA</a></li>
<li>Successful&#160;:&#160;<a class="el" href="structshark_1_1_c_m_a_chromosome.html#a1f218363002ca2397630da815462d207a2658107652dbc18fa1dfc1561bbc9d8d">shark::CMAChromosome</a></li>
<li>SufficientStatistics&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#a7765cfaf85d31f7a45dd31c55e6cf387">shark::BinaryLayer</a></li>
<li>sufficientStatistics()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#a9ce67738aea657cfba6131af44a6c0f1">shark::BinaryLayer</a></li>
<li>SufficientStatistics&#160;:&#160;<a class="el" href="classshark_1_1_bipolar_layer.html#a50437ba2ec0d1b49fa5cab84f008fb0a">shark::BipolarLayer</a></li>
<li>sufficientStatistics()&#160;:&#160;<a class="el" href="classshark_1_1_bipolar_layer.html#ab5ddcf9ae8d0e60b1570131409795857">shark::BipolarLayer</a></li>
<li>SufficientStatistics&#160;:&#160;<a class="el" href="classshark_1_1_gaussian_layer.html#a4c79a6809fa54a8788fc9a73f9661759">shark::GaussianLayer</a></li>
<li>sufficientStatistics()&#160;:&#160;<a class="el" href="classshark_1_1_gaussian_layer.html#a0e768ac30ba61b25220fa17293591d0c">shark::GaussianLayer</a></li>
<li>suggestLambda()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#afc7fa629a06f22c0f1cb09ca8c7cedd2">shark::CMA</a>, <a class="el" href="classshark_1_1_l_m_c_m_a.html#a8846e369c997015e1759d7ce315a3563">shark::LMCMA</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#aa745975f4a9c3349eaf9a2ebbc2a876a">shark::VDCMA</a></li>
<li>suggestMu()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#aa4b806974a96ecb62991bd8b5f88ae69">shark::CMA</a>, <a class="el" href="classshark_1_1_l_m_c_m_a.html#aa9751cb33edf7452cee4984f1c5fb2e7">shark::LMCMA</a>, <a class="el" href="classshark_1_1_r_v_e_a.html#af24f818da10910dabfbbb1028df31bbb">shark::RVEA</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#a3d4aaa6f933f6658d22d046ecc0023ee">shark::VDCMA</a></li>
<li>suggestPopulationSize()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#adad84b965331a4c66edf77b64a03532d">shark::CrossEntropyMethod</a></li>
<li>suggestSelectionSize()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#a9d185dcc48d6f045bb5bdb278c2d90ee">shark::CrossEntropyMethod</a></li>
<li>sumOfWeights()&#160;:&#160;<a class="el" href="classshark_1_1_ensemble.html#a6965c4363321584b44389670044d24bd">shark::Ensemble&lt; ModelType, OutputType &gt;</a></li>
<li>super&#160;:&#160;<a class="el" href="classshark_1_1_combined_objective_function.html#a4d4eafb7d559cd021d3f00fcc99106dd">shark::CombinedObjectiveFunction&lt; SearchPointType, ResultT &gt;</a></li>
<li>SUPERLINEAR&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#aafbd8e245dd9f8aad0e0e597557c9eb3a791798e0145d16d584a2bbb7d2deddb7">shark::CMA</a></li>
<li>SUPPORTS_VARIABLE_INPUT_SIZE&#160;:&#160;<a class="el" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae04fd78a7baf17b1591cdb6ef289e8d1">shark::AbstractKernelFunction&lt; InputTypeT &gt;</a></li>
<li>supportsVariableInputSize()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_kernel_function.html#a225fbad3a0efdac21e4422576de2ce4e">shark::AbstractKernelFunction&lt; InputTypeT &gt;</a></li>
<li>SvmLogisticInterpretation()&#160;:&#160;<a class="el" href="classshark_1_1_svm_logistic_interpretation.html#acd0536c312b58338f044a8d655d8739a">shark::SvmLogisticInterpretation&lt; InputType &gt;</a></li>
<li>SvmProblem()&#160;:&#160;<a class="el" href="classshark_1_1_svm_problem.html#ad10f8907862c01b1fc4ec5cd0ff06823">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>SvmShrinkingProblem()&#160;:&#160;<a class="el" href="classshark_1_1_svm_shrinking_problem.html#a520bb3904668c9c62b43aad128ada107">shark::SvmShrinkingProblem&lt; Problem &gt;</a></li>
<li>swap&#160;:&#160;<a class="el" href="group__shark__globals.html#ga54bdb86caca27a90ce28a8043fe4bced">shark::Data&lt; Type &gt;</a>, <a class="el" href="classshark_1_1_individual.html#a94637c55f4ded98f7e17bcbb7727da92">shark::Individual&lt; PointType, FitnessTypeT, Chromosome &gt;</a>, <a class="el" href="group__shark__globals.html#gaa3cac8411f8423f5de504e86e4ef8291">shark::LabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="structshark_1_1_result_set.html#a01d217c4e9ac5a62eb097eeeab97b4fe">shark::ResultSet&lt; SearchPointT, ResultT &gt;</a>, <a class="el" href="classshark_1_1_weighted_labeled_data.html#a3379551f7a879a2ed49dd6046024dcf3">shark::WeightedLabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="classshark_1_1_weighted_unlabeled_data.html#aac37ab4ee3db2b92d744146f176b43c2">shark::WeightedUnlabeledData&lt; DataT &gt;</a></li>
<li>swapLineIndices()&#160;:&#160;<a class="el" href="classshark_1_1_l_r_u_cache.html#af995657d3a4cd3c7c85550e0fb056985">shark::LRUCache&lt; T &gt;</a></li>
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